A typical enterprise in today's highly automated environment can have a variety of systems and data sources. Each system can produce different versions of the same data types that the enterprise manages and tracks. So, similar or same data is often repetitively stored within the enterprise. In fact, with some data sources the information may be incomplete whereas in other data sources the information may be more robust.
The above situation occurs for a variety of reasons. Most notably, as technology evolves an enterprise may find it more convenient and more efficient, at a particular point in time, to simply replicate some data sources rather then undergo expensive porting exercises to make newer systems and older systems compatible with one another. Over time, the enterprise can end up with data sources and systems that begin to impair the effectiveness of the enterprise. The enterprise may then undergo expensive and time consuming internal fabrication overhauls to bring their infrastructure up-to-data and make it more competitive with the industry. In fact, such scenarios are part of the normal lifecycle of today's enterprises.
One problem with internal infrastructure overhauls is that they can be so large that by the time they finish, the enterprise needs to begin yet another overhaul. The capital expense and human effort that it takes for these overhauls can significantly alter an enterprise's financial picture on its annual report.
Furthermore, enterprises generally do not have an automated mechanism to view and analyze all its enterprise information in a single robust and automated fashion. This means that a plurality of disparate management, support, analysis, and report tools are needed within the enterprise. Moreover, even if such an automated mechanism did exist there is still no mechanism that permits the automated transformation between the various data sources; so, a huge manual effort is often still needed to keep enterprise information in synchronization.
Thus, improved and automated techniques are needed enterprise data management and analysis.